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Engineering a series of Scaffold-associated isoprenol utilization pathways to enhance terpene production spanning diverse chain lengths.

Jul 2026 · Bioresource Technology · pp. 135414 · 0 citations · 37 references
Medicine

Abstract

Terpenoids are valuable resources for pharmaceutical research, yet their natural supply remains constrained. While the artificial isoprenol utilization pathway (IUP) has emerged as a promising alternative for terpene precursor supply, its full potential is limited by suboptimal pathway flux and substrate tolerance. Here, we report an efficient scaffold-assisted IUP platform tailored for high-throughput terpenoid discovery and scalable production. By recruiting rate-limiting IUP enzymes and prenyltransferases (PTs) onto self-assembling PduA* protein scaffolds displaying CC-Di-B peptides that specifically interact with CC-Di-A-tagged enzymes, we achieved spatial organization of the biosynthetic machinery. Systematic optimization of promoter configuration, fermentation conditions, and enzyme fusion yielded the optimal system ScMKI4-GS, achieving gram-per-liter-scale production (1.1 g/L) of the eunicellane-type diterpene benditerpe-2,6,15-triene in simple shake-flask fermentation-substantially outperforming scaffold-free controls. The platform demonstrated broad applicability across five structurally distinct eunicellane synthases, with each exhibiting enhanced production upon scaffold incorporation. For lycopene biosynthesis, the scaffold-assisted system produced 729.7 mg/L-a 9-fold improvement over the canonical MVA pathway under identical conditions, representing the highest IUP-based lycopene titer reported in Escherichia coli to date. Finally, by systematic substitution of chain-length-specific PTs, we expanded the platform to efficiently generate C10-C35 terpene precursors, facilitating functional characterization of terpene-related genes. Collectively, this versatile scaffold-assisted IUP platform provides a robust tool to expand terpenoid structural diversity and accelerate their scalable overproduction.

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